Immersive Inspection: Intuitive Material Analysis using X-Ray Computed Tomography Data in AR

IF 2.4 3区 材料科学 Q2 MATERIALS SCIENCE, CHARACTERIZATION & TESTING
Alexander Gall, Anja Heim, Patrick Weinberger, Bernhard Fröhler, Johann Kastner, Christoph Heinzl
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引用次数: 0

Abstract

Material analyses based on X-ray computed tomography (XCT) imaging are typically conducted away from scanning facilities, in separate office environments on 2D displays. This separation hinders on-site analysis, and due to the lack of spatial representation, limits the effective exploration of the material structure. We present a novel augmented reality (AR) framework enabling in-situ visualization of non-destructive testing (NDT) data spatially registered with real specimens. Our approach facilitates comprehensive exploration of primary and secondary XCT data, enabling researchers to inspect material properties onsite and in-place. Coupling immersive visualization techniques with real physical objects allows for highly intuitive workflows in material analysis and inspection, which enables the identification of anomalies and accelerates informed decision making. The AR framework offers automatic material recognition, hands-free workflows and embodied interaction with physical samples, generating an engaging analytical experience. A case study on fiber-reinforced polymer datasets was used to validate the AR framework and its new workflow. Expert evaluations revealed significant improvements in spatial data comprehension and more natural interaction compared to conventional analysis systems. This study demonstrates the potential of immersive AR technologies to enhance industrial materials analysis, providing preliminary insights for integrating such immersive approaches.

沉浸式检测:使用AR中的x射线计算机断层扫描数据进行直观的材料分析
基于x射线计算机断层扫描(XCT)成像的材料分析通常远离扫描设备,在单独的办公环境中使用2D显示器进行。这种分离阻碍了现场分析,并且由于缺乏空间表征,限制了对材料结构的有效探索。我们提出了一种新的增强现实(AR)框架,能够将无损检测(NDT)数据在空间上与真实样品进行注册。我们的方法有助于全面探索初级和次级XCT数据,使研究人员能够在现场和现场检查材料特性。将沉浸式可视化技术与真实的物理对象相结合,可以在材料分析和检查中实现高度直观的工作流程,从而能够识别异常并加速知情决策。AR框架提供自动材料识别、免提工作流程以及与物理样品的具体交互,从而产生引人入胜的分析体验。以纤维增强聚合物数据集为例,对AR框架及其新工作流程进行了验证。专家评估显示,与传统分析系统相比,空间数据理解能力有了显著提高,交互更加自然。这项研究展示了沉浸式AR技术在增强工业材料分析方面的潜力,为整合这种沉浸式方法提供了初步的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Nondestructive Evaluation
Journal of Nondestructive Evaluation 工程技术-材料科学:表征与测试
CiteScore
4.90
自引率
7.10%
发文量
67
审稿时长
9 months
期刊介绍: Journal of Nondestructive Evaluation provides a forum for the broad range of scientific and engineering activities involved in developing a quantitative nondestructive evaluation (NDE) capability. This interdisciplinary journal publishes papers on the development of new equipment, analyses, and approaches to nondestructive measurements.
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